PD-Bug: A Novel Motion Planning Algorithm for Nonholonomic Car-Like Robots in Unknown Environments

Fukang Xu, Xudong Zhang, Yuan Zou, Xin Yin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

In this work, we propose a novel motion planning algorithm for nonholonomic car-like robots in unknown environments. The proposed algorithm termed Polynomial spiral and Dubins path Bug (PD-Bug) is developed as a variant of TangentBug. Considering the errors of range measurements and the shape of a robot, an environment model termed local target set (LTS) is established to provide an optimal local target during each planning period. For localization errors, a more robust motion mode switching mechanism is integrated into PD-Bug. A lookup table for cubic polynomial spirals is generated offline, providing a smooth and optimized trajectory with curvature constraints. The Dubins path is generated online as the sub-optimal solution and utilized to meet the orientation requirement of the target. We validate the applicability of PD-Bug in outdoor scenarios with real-time requirements. Compared with the traditional Bug algorithms, PD-Bug has a significant improvement in the robustness of the motion mode and the smoothness of the trajectory.

Original languageEnglish
Title of host publication2021 5th CAA International Conference on Vehicular Control and Intelligence, CVCI 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665408462
DOIs
Publication statusPublished - 2021
Event5th CAA International Conference on Vehicular Control and Intelligence, CVCI 2021 - Tianjin, China
Duration: 29 Oct 202131 Oct 2021

Publication series

Name2021 5th CAA International Conference on Vehicular Control and Intelligence, CVCI 2021

Conference

Conference5th CAA International Conference on Vehicular Control and Intelligence, CVCI 2021
Country/TerritoryChina
CityTianjin
Period29/10/2131/10/21

Keywords

  • Bug algorithms
  • car-like robots
  • motion planning
  • unknown environments

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